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 Hyperledger-based blockchain system for peer-to-peer energy trading in electromobility systems
Journal article   Open access   Peer reviewed

Hyperledger-based blockchain system for peer-to-peer energy trading in electromobility systems

Idowu A. Ayoade and Omowunmi Mary Longe
IEEE access, Vol.14, pp.3943-3958
2026
Handle:
https://hdl.handle.net/10210/521753

Abstract

Artificial intelligence blockchain system Blockchains Costs DC-OPF Distributed ledger Electric vehicle charging EV charging Fabrics Hyperledger fabric locational marginal pricing peer-to-peer energy trading Pricing Privacy Security Vehicle-to-grid
Electromobility requires transactive coordination that respects distribution-network limits while preserving auditability and privacy. This study presents a reproducible peer-to-peer energy trading system that integrates a network-constrained market with permissioned blockchain settlement. The market solves a convex welfare program with linearised power-flow limits and recovers nodal prices from dual variables to match bids and offers and determine clear quantities. Settlement uses Hyperledger Fabric via the Gateway API, including proposal endorsement, ordering, validation, and commit notifications. Meter evidence is hashed and, when necessary, stored with private data collections. A co-simulation harness links MATLAB/Simulink and MATPOWER for feeder dynamics and price formation with chaincode and client logic for settlement. Three case studies are evaluated: an urban microgrid, a suburban microgrid, and a mobile electric-vehicle swarm. An Ethereum testnet serves as a public-chain baseline. In the testbed, a tuned Fabric configuration sustained approximately 1.6 to 1.7 thousand transactions per second, with a 99th-percentile submit-to-commit latency of near one second and full deadline compliance at a one-second clearing cadence. Energy delivery accuracy remained tight, Multi-Version Concurrency Control conflicts were low, and dynamic nodal prices reduced EV charging cost relative to a flat tariff while signalling congestion through predictable rent patterns. The contribution is a deployable blueprint that connects network economics to verifiable settlement, featuring an open repository, benchmarking artifacts, and practical targets for endorsement width, block size, and timeouts. It also provides clear pathways to field trials, stochastic and robust clearing, zero-knowledge meter proofs, and city-scale deployment.
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url
https://doi.org/10.1109/ACCESS.2025.3650525View
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